Changes in Student Well-Being during the First School Year of the COVID-19 Pandemic: Impacts of School Closures and Learning Modality
Bibliographic record
Abstract
The COVID-19 pandemic significantly disrupted adolescents’ physical, social, and academic lives. Due to this, how adolescents’ well-being was impacted during the COVID-19 pandemic has been a top priority within research, but results produced have been inconsistent regarding the types of symptoms experienced and the severity. Therefore, the current study aims to answer how adolescent well-being (behavioural concerns and adaptive functioning) was impacted during the first school year of the COVID-19 pandemic, specifically during periods of school closures and in relation to learning modality. The current study used a longitudinal dataset from Alberta, Canada of participants aged 12 to 18, N = 911. At four timepoints between September 2020 and June 2021, students reported information on demographics and learning modality (in-person, virtual, and hybrid). Additionally, youth completed the Behaviour Intervention Monitoring Assessment System (BIMAS-2), a measure of behavioural concerns (negative affect, cognition/attention concerns, conduct behaviours) and adaptive functioning (social and academic functioning). Using LGM and RM MANCOVA/ANCOVA analyses, results indicated that from September 2020 to June 2021 negative affect and cognition/attention concerns increased, albeit scores continued to fall into a non-clinical range. Females endorsed higher rates of all behavioural concerns, and poorer social functioning. Further, students whose parents completed higher levels of education endorsed higher adaptive functioning. School closures had minimal impacts to well-being. Finally, learning modality was not associated with changes in behavioural concerns but receiving in-person education had some effects on social functioning and academic achievement. These results indicate that while there were some decreases in well-being, overall, youth were resilient. This information may be relevant to apply to short-term periods of online/hybrid learning and to use in cases where school closures are required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".